User-generated v/s designer-generated products

(This post is based on the article: User-generated versus designer-generated products: A performance assessment at Muji by Nishikawa, H., Schreier, M., & Ogawa, S.)In the course Customer Centric Digital Commerce we learn that one of the main reasons for empowering their user communities into the process is to generate new ideas. The authors of this article present a unique data set gathered from the Japanese consumer goods brand Muji, which has drawn on both sources of ideas (user-generated & designer-generated products) in parallel in recent years.

Muji is a Japanese manufacturer and retailer brand of a broad range of consumer goods, with a particular focus on interior and household products. Their products are sold in almost 500 Muji stores in 22 countries. The researchers focused only on the furniture division (20% of Muji’s total sales) and therefore they minimized the potential of confounding effects that arise from comparing different product categories. The observation period was from February 2005 to July 2009 and 43 new products were developed, produced, and introduced to the Japanese market. 37 products were designer-generated, and 6 were user-generated.

Muji invites users to generate ideas for new products. Anyone who registers on their website can participate. Similar to the internal development of designer-generated products, idea generation follows a specific theme (for example limited storage capacity in consumers’ bedrooms due to small room sizes) for which solutions can be proposed.

The Muji firm’s study takes the form of crowd contest, which entail that the participants compete for the price. However, interestingly after the first stage the other users can also comment, vote, and improve on each other’s ideas. This last give the crowdsourcing some degree of the collaboration type.

Their results show an enumeration of performance metrics on which user-generated products were likely superior to internally-generated products:
–Total unit sales: 1st year: twice as much as designer-generated products (DGP). 3years: three times more frequently than DGP.
–Total sales revenue:1st year: more than three times higher than those of DGP. 3years: Over five times the sales of DGP.
–Gross margin:1st year: Four times higher than DGP. 3years: Six times greater, than DGP.
–Survival likelihood, Novelty and strategic impact: 1st year: “worst” user-generated product has a strategic impact score close to the average score of designer-generated products. In addition, they outperformed the DGP after 3 years.
–Market Performance: Only 17 out of 37 designer-generated products were still on the shelves after three years. In contrast, five out of six user-generated products were still on the market.

Summarizing, this study demonstrate that user-generated products systematically and substantially outperform their designer-generated counterparts in terms of key market performance metrics. However, in their discussion, the authors claim that firms should draw on user ideas in parallel to their established in-house efforts. The overall NPD process entails many more stages, and that decisive in-house efforts and capabilities are needed to convert any promising idea into a successful new product.

In addition, they also conclude that their results show that user-generated products are more complex and takes more times to implement and this last is especially shown in the amount of user generated v/s designer-generated products in the observation period.
The authors claim that one important question that remained unanswered after their study is: What are the specific capabilities that make user-driven firms successful?